Embedded Vision Foundations: Building Intelligent Systems: A Project-Based Guide to Low-Power Computer Vision and Real-Time Image Processing
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Imported Edition - Ships in 18-21 Days
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The Cloud is Too Slow. The Future is at the Edge.
Stop sending your data to the cloud and start processing it at the source. In the high-stakes world of modern engineering, the real innovation isn't happening in massive data centers, it's happening on the "Edge." Whether it's a remote security drone, an industrial quality-control sensor, or a privacy-first smart home device, the demand for Low-Power Computer Vision has never been higher.
Embedded Vision Foundations is your definitive, project-based blueprint for building decentralized intelligence from the ground up.
If you've ever struggled with choppy video streams, massive latency, or the sheer complexity of squeezing a neural network onto a tiny chip, this book is for you. Brian C. Ryan strips away the fluff and delivers a high-performance roadmap to mastering the ESP32-CAM and the OV2640 sensor.
Why this book is a must-have for your workbench:The Hardware Deep-Dive: Master the anatomy of the ESP32-CAM, from pinouts to power rails, and avoid the common pitfalls that fry boards.
Real-Time Processing: Implement frame-differencing and motion detection algorithms that run entirely on-device.
Optimized Architectures: Learn to build MJPEG streaming servers and handle DMA (Direct Memory Access) for lightning-fast image handling.
Engineering for the Wild: Deploy solar-ready, battery-optimized systems designed for months of autonomous operation.
The TinyML Bridge: Lay the essential foundation for neural networks and object detection (setting the stage for Book 2).
Embedded Vision Foundations doesn't just teach you how to write code; it teaches you how to think like a Systems Architect. By the end of this guide, you won't just have a working camera, you'll have a secure, efficient, and intelligent vision node ready for the real world.
Perfect for:Embedded Engineers looking to transition into the Edge AI niche.
Computer Science Students who want practical, hardware-integrated CV experience.
Innovation Leaders needing a privacy-centric alternative to cloud-based AI.
Don't build a device that just records data. Build a system that understands it.
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